• Imagine a world where CPUs are just fancy memory chips playing dress-up. Welcome to the latest trend in computer design: "Designing a CPU with only Memory Chips." Because, clearly, who needs the complexities of a processor when we can just stack bits of memory and call it a day?

    Forget about understanding the fundamentals of computing; let’s just embrace the chaos of a glorified memory buffet. Why learn about architecture when you can throw everything into RAM and see what sticks? It’s like trying to bake a cake with only flour—sure, it’s an interesting experiment, but you might just end up with a big, unappetizing mess.

    But hey, at least it’s simple, right?

    #MemoryCh
    Imagine a world where CPUs are just fancy memory chips playing dress-up. Welcome to the latest trend in computer design: "Designing a CPU with only Memory Chips." Because, clearly, who needs the complexities of a processor when we can just stack bits of memory and call it a day? 🎉 Forget about understanding the fundamentals of computing; let’s just embrace the chaos of a glorified memory buffet. Why learn about architecture when you can throw everything into RAM and see what sticks? It’s like trying to bake a cake with only flour—sure, it’s an interesting experiment, but you might just end up with a big, unappetizing mess. But hey, at least it’s simple, right? #MemoryCh
    Designing a CPU with only Memory Chips
    hackaday.com
    Building a simple 8-bit computer is a great way to understand computing fundamentals, but there’s only so much you can learn by building a system around an existing processor. If …read more
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  • Rewriting SymCrypt in Rust to modernize Microsoft’s cryptographic library 

    Outdated coding practices and memory-unsafe languages like C are putting software, including cryptographic libraries, at risk. Fortunately, memory-safe languages like Rust, along with formal verification tools, are now mature enough to be used at scale, helping prevent issues like crashes, data corruption, flawed implementation, and side-channel attacks.
    To address these vulnerabilities and improve memory safety, we’re rewriting SymCrypt—Microsoft’s open-source cryptographic library—in Rust. We’re also incorporating formal verification methods. SymCrypt is used in Windows, Azure Linux, Xbox, and other platforms.
    Currently, SymCrypt is primarily written in cross-platform C, with limited use of hardware-specific optimizations through intrinsicsand assembly language. It provides a wide range of algorithms, including AES-GCM, SHA, ECDSA, and the more recent post-quantum algorithms ML-KEM and ML-DSA. 
    Formal verification will confirm that implementations behave as intended and don’t deviate from algorithm specifications, critical for preventing attacks. We’ll also analyze compiled code to detect side-channel leaks caused by timing or hardware-level behavior.
    Proving Rust program properties with Aeneas
    Program verification is the process of proving that a piece of code will always satisfy a given property, no matter the input. Rust’s type system profoundly improves the prospects for program verification by providing strong ownership guarantees, by construction, using a discipline known as “aliasing xor mutability”.
    For example, reasoning about C code often requires proving that two non-const pointers are live and non-overlapping, a property that can depend on external client code. In contrast, Rust’s type system guarantees this property for any two mutably borrowed references.
    As a result, new tools have emerged specifically for verifying Rust code. We chose Aeneasbecause it helps provide a clean separation between code and proofs.
    Developed by Microsoft Azure Research in partnership with Inria, the French National Institute for Research in Digital Science and Technology, Aeneas connects to proof assistants like Lean, allowing us to draw on a large body of mathematical proofs—especially valuable given the mathematical nature of cryptographic algorithms—and benefit from Lean’s active user community.
    Compiling Rust to C supports backward compatibility  
    We recognize that switching to Rust isn’t feasible for all use cases, so we’ll continue to support, extend, and certify C-based APIs as long as users need them. Users won’t see any changes, as Rust runs underneath the existing C APIs.
    Some users compile our C code directly and may rely on specific toolchains or compiler features that complicate the adoption of Rust code. To address this, we will use Eurydice, a Rust-to-C compiler developed by Microsoft Azure Research, to replace handwritten C code with C generated from formally verified Rust. Eurydicecompiles directly from Rust’s MIR intermediate language, and the resulting C code will be checked into the SymCrypt repository alongside the original Rust source code.
    As more users adopt Rust, we’ll continue supporting this compilation path for those who build SymCrypt from source code but aren’t ready to use the Rust compiler. In the long term, we hope to transition users to either use precompiled SymCrypt binaries, or compile from source code in Rust, at which point the Rust-to-C compilation path will no longer be needed.

    Microsoft research podcast

    Ideas: AI and democracy with Madeleine Daepp and Robert Osazuwa Ness
    As the “biggest election year in history” comes to an end, researchers Madeleine Daepp and Robert Osazuwa Ness and Democracy Forward GM Ginny Badanes discuss AI’s impact on democracy, including the tech’s use in Taiwan and India.

    Listen now

    Opens in a new tab
    Timing analysis with Revizor 
    Even software that has been verified for functional correctness can remain vulnerable to low-level security threats, such as side channels caused by timing leaks or speculative execution. These threats operate at the hardware level and can leak private information, such as memory load addresses, branch targets, or division operands, even when the source code is provably correct. 
    To address this, we’re extending Revizor, a tool developed by Microsoft Azure Research, to more effectively analyze SymCrypt binaries. Revizor models microarchitectural leakage and uses fuzzing techniques to systematically uncover instructions that may expose private information through known hardware-level effects.  
    Earlier cryptographic libraries relied on constant-time programming to avoid operations on secret data. However, recent research has shown that this alone is insufficient with today’s CPUs, where every new optimization may open a new side channel. 
    By analyzing binary code for specific compilers and platforms, our extended Revizor tool enables deeper scrutiny of vulnerabilities that aren’t visible in the source code.
    Verified Rust implementations begin with ML-KEM
    This long-term effort is in alignment with the Microsoft Secure Future Initiative and brings together experts across Microsoft, building on decades of Microsoft Research investment in program verification and security tooling.
    A preliminary version of ML-KEM in Rust is now available on the preview feature/verifiedcryptobranch of the SymCrypt repository. We encourage users to try the Rust build and share feedback. Looking ahead, we plan to support direct use of the same cryptographic library in Rust without requiring C bindings. 
    Over the coming months, we plan to rewrite, verify, and ship several algorithms in Rust as part of SymCrypt. As our investment in Rust deepens, we expect to gain new insights into how to best leverage the language for high-assurance cryptographic implementations with low-level optimizations. 
    As performance is key to scalability and sustainability, we’re holding new implementations to a high bar using our benchmarking tools to match or exceed existing systems.
    Looking forward 
    This is a pivotal moment for high-assurance software. Microsoft’s investment in Rust and formal verification presents a rare opportunity to advance one of our key libraries. We’re excited to scale this work and ultimately deliver an industrial-grade, Rust-based, FIPS-certified cryptographic library.
    Opens in a new tab
    #rewriting #symcrypt #rust #modernize #microsofts
    Rewriting SymCrypt in Rust to modernize Microsoft’s cryptographic library 
    Outdated coding practices and memory-unsafe languages like C are putting software, including cryptographic libraries, at risk. Fortunately, memory-safe languages like Rust, along with formal verification tools, are now mature enough to be used at scale, helping prevent issues like crashes, data corruption, flawed implementation, and side-channel attacks. To address these vulnerabilities and improve memory safety, we’re rewriting SymCrypt—Microsoft’s open-source cryptographic library—in Rust. We’re also incorporating formal verification methods. SymCrypt is used in Windows, Azure Linux, Xbox, and other platforms. Currently, SymCrypt is primarily written in cross-platform C, with limited use of hardware-specific optimizations through intrinsicsand assembly language. It provides a wide range of algorithms, including AES-GCM, SHA, ECDSA, and the more recent post-quantum algorithms ML-KEM and ML-DSA.  Formal verification will confirm that implementations behave as intended and don’t deviate from algorithm specifications, critical for preventing attacks. We’ll also analyze compiled code to detect side-channel leaks caused by timing or hardware-level behavior. Proving Rust program properties with Aeneas Program verification is the process of proving that a piece of code will always satisfy a given property, no matter the input. Rust’s type system profoundly improves the prospects for program verification by providing strong ownership guarantees, by construction, using a discipline known as “aliasing xor mutability”. For example, reasoning about C code often requires proving that two non-const pointers are live and non-overlapping, a property that can depend on external client code. In contrast, Rust’s type system guarantees this property for any two mutably borrowed references. As a result, new tools have emerged specifically for verifying Rust code. We chose Aeneasbecause it helps provide a clean separation between code and proofs. Developed by Microsoft Azure Research in partnership with Inria, the French National Institute for Research in Digital Science and Technology, Aeneas connects to proof assistants like Lean, allowing us to draw on a large body of mathematical proofs—especially valuable given the mathematical nature of cryptographic algorithms—and benefit from Lean’s active user community. Compiling Rust to C supports backward compatibility   We recognize that switching to Rust isn’t feasible for all use cases, so we’ll continue to support, extend, and certify C-based APIs as long as users need them. Users won’t see any changes, as Rust runs underneath the existing C APIs. Some users compile our C code directly and may rely on specific toolchains or compiler features that complicate the adoption of Rust code. To address this, we will use Eurydice, a Rust-to-C compiler developed by Microsoft Azure Research, to replace handwritten C code with C generated from formally verified Rust. Eurydicecompiles directly from Rust’s MIR intermediate language, and the resulting C code will be checked into the SymCrypt repository alongside the original Rust source code. As more users adopt Rust, we’ll continue supporting this compilation path for those who build SymCrypt from source code but aren’t ready to use the Rust compiler. In the long term, we hope to transition users to either use precompiled SymCrypt binaries, or compile from source code in Rust, at which point the Rust-to-C compilation path will no longer be needed. Microsoft research podcast Ideas: AI and democracy with Madeleine Daepp and Robert Osazuwa Ness As the “biggest election year in history” comes to an end, researchers Madeleine Daepp and Robert Osazuwa Ness and Democracy Forward GM Ginny Badanes discuss AI’s impact on democracy, including the tech’s use in Taiwan and India. Listen now Opens in a new tab Timing analysis with Revizor  Even software that has been verified for functional correctness can remain vulnerable to low-level security threats, such as side channels caused by timing leaks or speculative execution. These threats operate at the hardware level and can leak private information, such as memory load addresses, branch targets, or division operands, even when the source code is provably correct.  To address this, we’re extending Revizor, a tool developed by Microsoft Azure Research, to more effectively analyze SymCrypt binaries. Revizor models microarchitectural leakage and uses fuzzing techniques to systematically uncover instructions that may expose private information through known hardware-level effects.   Earlier cryptographic libraries relied on constant-time programming to avoid operations on secret data. However, recent research has shown that this alone is insufficient with today’s CPUs, where every new optimization may open a new side channel.  By analyzing binary code for specific compilers and platforms, our extended Revizor tool enables deeper scrutiny of vulnerabilities that aren’t visible in the source code. Verified Rust implementations begin with ML-KEM This long-term effort is in alignment with the Microsoft Secure Future Initiative and brings together experts across Microsoft, building on decades of Microsoft Research investment in program verification and security tooling. A preliminary version of ML-KEM in Rust is now available on the preview feature/verifiedcryptobranch of the SymCrypt repository. We encourage users to try the Rust build and share feedback. Looking ahead, we plan to support direct use of the same cryptographic library in Rust without requiring C bindings.  Over the coming months, we plan to rewrite, verify, and ship several algorithms in Rust as part of SymCrypt. As our investment in Rust deepens, we expect to gain new insights into how to best leverage the language for high-assurance cryptographic implementations with low-level optimizations.  As performance is key to scalability and sustainability, we’re holding new implementations to a high bar using our benchmarking tools to match or exceed existing systems. Looking forward  This is a pivotal moment for high-assurance software. Microsoft’s investment in Rust and formal verification presents a rare opportunity to advance one of our key libraries. We’re excited to scale this work and ultimately deliver an industrial-grade, Rust-based, FIPS-certified cryptographic library. Opens in a new tab #rewriting #symcrypt #rust #modernize #microsofts
    Rewriting SymCrypt in Rust to modernize Microsoft’s cryptographic library 
    www.microsoft.com
    Outdated coding practices and memory-unsafe languages like C are putting software, including cryptographic libraries, at risk. Fortunately, memory-safe languages like Rust, along with formal verification tools, are now mature enough to be used at scale, helping prevent issues like crashes, data corruption, flawed implementation, and side-channel attacks. To address these vulnerabilities and improve memory safety, we’re rewriting SymCrypt (opens in new tab)—Microsoft’s open-source cryptographic library—in Rust. We’re also incorporating formal verification methods. SymCrypt is used in Windows, Azure Linux, Xbox, and other platforms. Currently, SymCrypt is primarily written in cross-platform C, with limited use of hardware-specific optimizations through intrinsics (compiler-provided low-level functions) and assembly language (direct processor instructions). It provides a wide range of algorithms, including AES-GCM, SHA, ECDSA, and the more recent post-quantum algorithms ML-KEM and ML-DSA.  Formal verification will confirm that implementations behave as intended and don’t deviate from algorithm specifications, critical for preventing attacks. We’ll also analyze compiled code to detect side-channel leaks caused by timing or hardware-level behavior. Proving Rust program properties with Aeneas Program verification is the process of proving that a piece of code will always satisfy a given property, no matter the input. Rust’s type system profoundly improves the prospects for program verification by providing strong ownership guarantees, by construction, using a discipline known as “aliasing xor mutability”. For example, reasoning about C code often requires proving that two non-const pointers are live and non-overlapping, a property that can depend on external client code. In contrast, Rust’s type system guarantees this property for any two mutably borrowed references. As a result, new tools have emerged specifically for verifying Rust code. We chose Aeneas (opens in new tab) because it helps provide a clean separation between code and proofs. Developed by Microsoft Azure Research in partnership with Inria, the French National Institute for Research in Digital Science and Technology, Aeneas connects to proof assistants like Lean (opens in new tab), allowing us to draw on a large body of mathematical proofs—especially valuable given the mathematical nature of cryptographic algorithms—and benefit from Lean’s active user community. Compiling Rust to C supports backward compatibility   We recognize that switching to Rust isn’t feasible for all use cases, so we’ll continue to support, extend, and certify C-based APIs as long as users need them. Users won’t see any changes, as Rust runs underneath the existing C APIs. Some users compile our C code directly and may rely on specific toolchains or compiler features that complicate the adoption of Rust code. To address this, we will use Eurydice (opens in new tab), a Rust-to-C compiler developed by Microsoft Azure Research, to replace handwritten C code with C generated from formally verified Rust. Eurydice (opens in new tab) compiles directly from Rust’s MIR intermediate language, and the resulting C code will be checked into the SymCrypt repository alongside the original Rust source code. As more users adopt Rust, we’ll continue supporting this compilation path for those who build SymCrypt from source code but aren’t ready to use the Rust compiler. In the long term, we hope to transition users to either use precompiled SymCrypt binaries (via C or Rust APIs), or compile from source code in Rust, at which point the Rust-to-C compilation path will no longer be needed. Microsoft research podcast Ideas: AI and democracy with Madeleine Daepp and Robert Osazuwa Ness As the “biggest election year in history” comes to an end, researchers Madeleine Daepp and Robert Osazuwa Ness and Democracy Forward GM Ginny Badanes discuss AI’s impact on democracy, including the tech’s use in Taiwan and India. Listen now Opens in a new tab Timing analysis with Revizor  Even software that has been verified for functional correctness can remain vulnerable to low-level security threats, such as side channels caused by timing leaks or speculative execution. These threats operate at the hardware level and can leak private information, such as memory load addresses, branch targets, or division operands, even when the source code is provably correct.  To address this, we’re extending Revizor (opens in new tab), a tool developed by Microsoft Azure Research, to more effectively analyze SymCrypt binaries. Revizor models microarchitectural leakage and uses fuzzing techniques to systematically uncover instructions that may expose private information through known hardware-level effects.   Earlier cryptographic libraries relied on constant-time programming to avoid operations on secret data. However, recent research has shown that this alone is insufficient with today’s CPUs, where every new optimization may open a new side channel.  By analyzing binary code for specific compilers and platforms, our extended Revizor tool enables deeper scrutiny of vulnerabilities that aren’t visible in the source code. Verified Rust implementations begin with ML-KEM This long-term effort is in alignment with the Microsoft Secure Future Initiative and brings together experts across Microsoft, building on decades of Microsoft Research investment in program verification and security tooling. A preliminary version of ML-KEM in Rust is now available on the preview feature/verifiedcrypto (opens in new tab) branch of the SymCrypt repository. We encourage users to try the Rust build and share feedback (opens in new tab). Looking ahead, we plan to support direct use of the same cryptographic library in Rust without requiring C bindings.  Over the coming months, we plan to rewrite, verify, and ship several algorithms in Rust as part of SymCrypt. As our investment in Rust deepens, we expect to gain new insights into how to best leverage the language for high-assurance cryptographic implementations with low-level optimizations.  As performance is key to scalability and sustainability, we’re holding new implementations to a high bar using our benchmarking tools to match or exceed existing systems. Looking forward  This is a pivotal moment for high-assurance software. Microsoft’s investment in Rust and formal verification presents a rare opportunity to advance one of our key libraries. We’re excited to scale this work and ultimately deliver an industrial-grade, Rust-based, FIPS-certified cryptographic library. Opens in a new tab
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  • Graphene thermal pad for AMD CPUs promises 17X better conductivity than thermal paste, 2X improvement over Thermal Grizzly

    Coracer has launched the GPE-01 graphene pads for AMD's AM5 processors.
    #graphene #thermal #pad #amd #cpus
    Graphene thermal pad for AMD CPUs promises 17X better conductivity than thermal paste, 2X improvement over Thermal Grizzly
    Coracer has launched the GPE-01 graphene pads for AMD's AM5 processors. #graphene #thermal #pad #amd #cpus
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  • Upcoming (serious) Web performance boost

    UpcomingWeb performance boostBy:
    Adam Scott5 June 2025Progress ReportSometimes, just adding a compiler flag can yield significant performance boosts. And that just happened.For about two years now, all major browsers have supported WASMSIMD. SIMD stands for “Single instruction, multiple data” and is a technology that permits CPUs to do some parallel computation, often speeding up the whole program. And that’s exactly why we tried it out recently.We got positive results.The need for performance on the WebThe Web platform is often overlooked as a viable target, because of its less-than-ideal environment and its perceived poor performance. And the perception is somewhat right: the Web environment has a lot of security-related quirks to take into account—the user needs to interact with a game frame before the browser allows it to play any sound1. Also, due to bandwidth and compatibility reasons, you rarely see high-fidelity games being played on a browser. Performance is better achieved when running software natively on the operating system.But don’t underestimate the potential of the Web platform. As I explained in broad terms at the talk I gave at the last GodotCon Boston 2025, the Web has caught up a lot since the days of Flash games. Not only are there more people playing Web games every year, but standards and browsers improve every year in functionality and in performance.And that’s why we are interested in using WASM SIMD.WASM SIMD BenchmarksOur resident benchmark expert Hugo Locurcioran the numbers for us on a stress test I made. We wanted to compare standard builds to builds with WASM SIMD enabled.Note: You may try to replicate his results, but be aware that he has a beast of a machine. Here are his PC’s specifications:CPU: Intel Core i9-13900KGPU: NVIDIA GeForce RTX 4090RAM: 64 GBSSD: Solidigm P44 Pro 2 TBOS: LinuxI built a Jolt physics stress test from a scene initially made by passivestar. By spawning more and more barrels into the contraption, we can easily test the performance difference between the WASM SIMD build and the other.Without WASM SIMDWith WASM SIMDImprovementTest linksLinkLink-Firefox 1382×Firefox 13810.17×*Chromium 1341.37×Chromium 13414.17×**Please note that once the physics engine enters a “spiral of death”, it is common for the framerate to drop to single digits, SIMD or not. These tests don’t prove 10× to 15× CPU computing speed improvements, but rather that games will be more resilient to framerate drops on the same machine in the same circumstances. The 1.5× to 2× numbers are more representative here of the performance gains by WASM SIMD.What it means for your gamesStarting with 4.5 dev 5, you can expect your Web games to run a little bit more smoothly, without having to do anything. Especially when things get chaotic. It isn’t a silver bullet for poorly optimized games, but it will help nonetheless. Also, note that it cannot do anything for GPU rendering bottlenecks.Be aware that the stress tests are meant by nature to only test the worst case scenarios, so you may not see such large improvements in normal circumstances. But it’s nice to see such stark improvements when the worst happens.AvailabilityFrom here on out, the 4.5 release official templates will only support WebAssembly SIMD-compatible browsers in order to keep the template sizes small. We generally aim to maintain compatibility with the oldest devices we can. But in this case, the performance gains are too large to ignore and the chances of users having browsers that are that far out of date is too small relative to the potential benefits.If you need to use non-SIMD templates, don’t fret. You can always build the Godot Editor and the engine templates without WebAssembly SIMD support by using the wasm_simd=no build option.What’s next?As I wrote in my last blog post, we’re currently working very hard to make C#/.NET exports a reality. We do have a promising prototype, we just need to make sure that it’s production-ready.I also mentioned in that article that I wanted to concentrate on improving our asset loading game. Preloading an entire game before even starting it hinders the ability to use Godot for commercial Web games. Once something is implemented to improve that issue, count on me to share the news with you.It’s either that, or we return to the old days of spam-webpages using the “Congratulations, you won!” sound effect when you least expect it. ↩
    #upcoming #serious #web #performance #boost
    Upcoming (serious) Web performance boost
    UpcomingWeb performance boostBy: Adam Scott5 June 2025Progress ReportSometimes, just adding a compiler flag can yield significant performance boosts. And that just happened.For about two years now, all major browsers have supported WASMSIMD. SIMD stands for “Single instruction, multiple data” and is a technology that permits CPUs to do some parallel computation, often speeding up the whole program. And that’s exactly why we tried it out recently.We got positive results.The need for performance on the WebThe Web platform is often overlooked as a viable target, because of its less-than-ideal environment and its perceived poor performance. And the perception is somewhat right: the Web environment has a lot of security-related quirks to take into account—the user needs to interact with a game frame before the browser allows it to play any sound1. Also, due to bandwidth and compatibility reasons, you rarely see high-fidelity games being played on a browser. Performance is better achieved when running software natively on the operating system.But don’t underestimate the potential of the Web platform. As I explained in broad terms at the talk I gave at the last GodotCon Boston 2025, the Web has caught up a lot since the days of Flash games. Not only are there more people playing Web games every year, but standards and browsers improve every year in functionality and in performance.And that’s why we are interested in using WASM SIMD.WASM SIMD BenchmarksOur resident benchmark expert Hugo Locurcioran the numbers for us on a stress test I made. We wanted to compare standard builds to builds with WASM SIMD enabled.Note: You may try to replicate his results, but be aware that he has a beast of a machine. Here are his PC’s specifications:CPU: Intel Core i9-13900KGPU: NVIDIA GeForce RTX 4090RAM: 64 GBSSD: Solidigm P44 Pro 2 TBOS: LinuxI built a Jolt physics stress test from a scene initially made by passivestar. By spawning more and more barrels into the contraption, we can easily test the performance difference between the WASM SIMD build and the other.Without WASM SIMDWith WASM SIMDImprovementTest linksLinkLink-Firefox 1382×Firefox 13810.17×*Chromium 1341.37×Chromium 13414.17×**Please note that once the physics engine enters a “spiral of death”, it is common for the framerate to drop to single digits, SIMD or not. These tests don’t prove 10× to 15× CPU computing speed improvements, but rather that games will be more resilient to framerate drops on the same machine in the same circumstances. The 1.5× to 2× numbers are more representative here of the performance gains by WASM SIMD.What it means for your gamesStarting with 4.5 dev 5, you can expect your Web games to run a little bit more smoothly, without having to do anything. Especially when things get chaotic. It isn’t a silver bullet for poorly optimized games, but it will help nonetheless. Also, note that it cannot do anything for GPU rendering bottlenecks.Be aware that the stress tests are meant by nature to only test the worst case scenarios, so you may not see such large improvements in normal circumstances. But it’s nice to see such stark improvements when the worst happens.AvailabilityFrom here on out, the 4.5 release official templates will only support WebAssembly SIMD-compatible browsers in order to keep the template sizes small. We generally aim to maintain compatibility with the oldest devices we can. But in this case, the performance gains are too large to ignore and the chances of users having browsers that are that far out of date is too small relative to the potential benefits.If you need to use non-SIMD templates, don’t fret. You can always build the Godot Editor and the engine templates without WebAssembly SIMD support by using the wasm_simd=no build option.What’s next?As I wrote in my last blog post, we’re currently working very hard to make C#/.NET exports a reality. We do have a promising prototype, we just need to make sure that it’s production-ready.I also mentioned in that article that I wanted to concentrate on improving our asset loading game. Preloading an entire game before even starting it hinders the ability to use Godot for commercial Web games. Once something is implemented to improve that issue, count on me to share the news with you.It’s either that, or we return to the old days of spam-webpages using the “Congratulations, you won!” sound effect when you least expect it. ↩ #upcoming #serious #web #performance #boost
    Upcoming (serious) Web performance boost
    godotengine.org
    Upcoming (serious) Web performance boostBy: Adam Scott5 June 2025Progress ReportSometimes, just adding a compiler flag can yield significant performance boosts. And that just happened.For about two years now, all major browsers have supported WASM (WebAssembly) SIMD. SIMD stands for “Single instruction, multiple data” and is a technology that permits CPUs to do some parallel computation, often speeding up the whole program. And that’s exactly why we tried it out recently.We got positive results.The need for performance on the WebThe Web platform is often overlooked as a viable target, because of its less-than-ideal environment and its perceived poor performance. And the perception is somewhat right: the Web environment has a lot of security-related quirks to take into account—the user needs to interact with a game frame before the browser allows it to play any sound1. Also, due to bandwidth and compatibility reasons, you rarely see high-fidelity games being played on a browser. Performance is better achieved when running software natively on the operating system.But don’t underestimate the potential of the Web platform. As I explained in broad terms at the talk I gave at the last GodotCon Boston 2025, the Web has caught up a lot since the days of Flash games. Not only are there more people playing Web games every year, but standards and browsers improve every year in functionality and in performance.And that’s why we are interested in using WASM SIMD.WASM SIMD BenchmarksOur resident benchmark expert Hugo Locurcio (better known as Calinou) ran the numbers for us on a stress test I made. We wanted to compare standard builds to builds with WASM SIMD enabled.Note: You may try to replicate his results, but be aware that he has a beast of a machine. Here are his PC’s specifications:CPU: Intel Core i9-13900KGPU: NVIDIA GeForce RTX 4090RAM: 64 GB (2×32 GB DDR5-5800 CL30)SSD: Solidigm P44 Pro 2 TBOS: Linux (Fedora 42)I built a Jolt physics stress test from a scene initially made by passivestar. By spawning more and more barrels into the contraption, we can easily test the performance difference between the WASM SIMD build and the other.Without WASM SIMDWith WASM SIMDImprovement (approx.)Test linksLinkLink-Firefox 138(“+100 barrels” 3 times)2×Firefox 138(“+100 barrels” 6 times)10.17×*Chromium 134(“+100 barrels” 3 times)1.37×Chromium 134(“+100 barrels” 6 times)14.17×**Please note that once the physics engine enters a “spiral of death”, it is common for the framerate to drop to single digits, SIMD or not. These tests don’t prove 10× to 15× CPU computing speed improvements, but rather that games will be more resilient to framerate drops on the same machine in the same circumstances. The 1.5× to 2× numbers are more representative here of the performance gains by WASM SIMD.What it means for your gamesStarting with 4.5 dev 5, you can expect your Web games to run a little bit more smoothly, without having to do anything. Especially when things get chaotic (for your CPU). It isn’t a silver bullet for poorly optimized games, but it will help nonetheless. Also, note that it cannot do anything for GPU rendering bottlenecks.Be aware that the stress tests are meant by nature to only test the worst case scenarios, so you may not see such large improvements in normal circumstances. But it’s nice to see such stark improvements when the worst happens.AvailabilityFrom here on out, the 4.5 release official templates will only support WebAssembly SIMD-compatible browsers in order to keep the template sizes small. We generally aim to maintain compatibility with the oldest devices we can. But in this case, the performance gains are too large to ignore and the chances of users having browsers that are that far out of date is too small relative to the potential benefits.If you need to use non-SIMD templates, don’t fret. You can always build the Godot Editor and the engine templates without WebAssembly SIMD support by using the wasm_simd=no build option.What’s next?As I wrote in my last blog post, we’re currently working very hard to make C#/.NET exports a reality. We do have a promising prototype, we just need to make sure that it’s production-ready.I also mentioned in that article that I wanted to concentrate on improving our asset loading game. Preloading an entire game before even starting it hinders the ability to use Godot for commercial Web games. Once something is implemented to improve that issue, count on me to share the news with you.It’s either that, or we return to the old days of spam-webpages using the “Congratulations, you won!” sound effect when you least expect it. ↩
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  • Alienware Aurora R16 RTX 5080 Gaming PCs Start at Just $2,450 Shipped

    Alienware is offering competitive prices on RTX 5080 equipped gaming PCs to kick off June. Right now you can pick up an Alienware Aurora R16 RTX 5080 gaming PC from shipped. This is a good price for a well-engineered gaming rig with powerful current generation components, 240mm AIO water cooling, and sensible airflow design that can handle 4K gaming at high frame rates. In the current market, buying a prebuilt gaming PC is the only way to score an RTX 5080 GPU without paying an exorbitant markup. If you were to try to find a 5080 GPU for your do-it-yourself PC build, you'll probably spend nearly as much for the GPU as you would for an entire system.Alienware Aurora RTX 5080 Gaming PC From Alienware Aurora R16 Intel Core Ultra 7 265F RTX 5080 Gaming PCat AlienwareAlienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PCAlienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PCNew for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PCThe prices on the Alienware Aurora R16 model starts range from the bottom end of to the top end of Each tier up offers either a CPU upgrade or increased RAM and/or storage:- Intel Core Ultra 7 265F, 16GB RAM, 1TB SSD- Intel Core Ultra 9 285K, 32GB RAM, 2TB SSD- Intel Core Ultra 9 285K, 64GB RAM, 4TB SSDAlienware Area-51 RTX 5080 Gaming PC for New for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PCDell unveiled the new Alienware Area-51 gaming PC at CES 2025. The chassis looks similar to the 2024 R16 system with aesthetic and cooling redesigns and updated components. The I/O panel is positioned at the top of the case instead of the front, and the tempered glass window now spans the entire side panel instead of just a smaller cutout. As a result, the side panel vents are gone, and instead air intakes are located at the bottom as well as the front of the case. Alienware is now pushing a positive airflow design, which means a less dusty interior. The internal components have been refreshed with a new motherboard, faster RAM, and more powerful power supply to accommodate the new generation of CPUs and GPUs.The GeForce RTX 5080 GPU will run any game in 4KThe RTX 5080 is the second best Blackwell graphics card, surpassed only by the RTX 5090. It's about 5%-10% faster than the previous generation RTX 4080 Super, which is discontinued and no longer available. In games that support the new DLSS 4 with multi-frame generation exclusive to Blackwell cards, the gap widens.Nvidia GeForce RTX 5080 FE Review, by Jacqueline Thomas"If you already have a high-end graphics card from the last couple of years, the Nvidia GeForce RTX 5080 doesn’t make a lot of sense – it just doesn’t have much of a performance lead over the RTX 4080, though the extra frames from DLSS 4 Multi-Frame Generation do make things look better in games that support it. However, for gamers with an older graphics card who want a significant performance boost, the RTX 5080 absolutely provides – doubly so if you’re comfortable with Nvidia’s AI goodies."Eric Song is the IGN commerce manager in charge of finding the best gaming and tech deals every day. When Eric isn't hunting for deals for other people at work, he's hunting for deals for himself during his free time.
    #alienware #aurora #r16 #rtx #gaming
    Alienware Aurora R16 RTX 5080 Gaming PCs Start at Just $2,450 Shipped
    Alienware is offering competitive prices on RTX 5080 equipped gaming PCs to kick off June. Right now you can pick up an Alienware Aurora R16 RTX 5080 gaming PC from shipped. This is a good price for a well-engineered gaming rig with powerful current generation components, 240mm AIO water cooling, and sensible airflow design that can handle 4K gaming at high frame rates. In the current market, buying a prebuilt gaming PC is the only way to score an RTX 5080 GPU without paying an exorbitant markup. If you were to try to find a 5080 GPU for your do-it-yourself PC build, you'll probably spend nearly as much for the GPU as you would for an entire system.Alienware Aurora RTX 5080 Gaming PC From Alienware Aurora R16 Intel Core Ultra 7 265F RTX 5080 Gaming PCat AlienwareAlienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PCAlienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PCNew for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PCThe prices on the Alienware Aurora R16 model starts range from the bottom end of to the top end of Each tier up offers either a CPU upgrade or increased RAM and/or storage:- Intel Core Ultra 7 265F, 16GB RAM, 1TB SSD- Intel Core Ultra 9 285K, 32GB RAM, 2TB SSD- Intel Core Ultra 9 285K, 64GB RAM, 4TB SSDAlienware Area-51 RTX 5080 Gaming PC for New for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PCDell unveiled the new Alienware Area-51 gaming PC at CES 2025. The chassis looks similar to the 2024 R16 system with aesthetic and cooling redesigns and updated components. The I/O panel is positioned at the top of the case instead of the front, and the tempered glass window now spans the entire side panel instead of just a smaller cutout. As a result, the side panel vents are gone, and instead air intakes are located at the bottom as well as the front of the case. Alienware is now pushing a positive airflow design, which means a less dusty interior. The internal components have been refreshed with a new motherboard, faster RAM, and more powerful power supply to accommodate the new generation of CPUs and GPUs.The GeForce RTX 5080 GPU will run any game in 4KThe RTX 5080 is the second best Blackwell graphics card, surpassed only by the RTX 5090. It's about 5%-10% faster than the previous generation RTX 4080 Super, which is discontinued and no longer available. In games that support the new DLSS 4 with multi-frame generation exclusive to Blackwell cards, the gap widens.Nvidia GeForce RTX 5080 FE Review, by Jacqueline Thomas"If you already have a high-end graphics card from the last couple of years, the Nvidia GeForce RTX 5080 doesn’t make a lot of sense – it just doesn’t have much of a performance lead over the RTX 4080, though the extra frames from DLSS 4 Multi-Frame Generation do make things look better in games that support it. However, for gamers with an older graphics card who want a significant performance boost, the RTX 5080 absolutely provides – doubly so if you’re comfortable with Nvidia’s AI goodies."Eric Song is the IGN commerce manager in charge of finding the best gaming and tech deals every day. When Eric isn't hunting for deals for other people at work, he's hunting for deals for himself during his free time. #alienware #aurora #r16 #rtx #gaming
    Alienware Aurora R16 RTX 5080 Gaming PCs Start at Just $2,450 Shipped
    www.ign.com
    Alienware is offering competitive prices on RTX 5080 equipped gaming PCs to kick off June. Right now you can pick up an Alienware Aurora R16 RTX 5080 gaming PC from $2,449.99 shipped. This is a good price for a well-engineered gaming rig with powerful current generation components, 240mm AIO water cooling, and sensible airflow design that can handle 4K gaming at high frame rates. In the current market, buying a prebuilt gaming PC is the only way to score an RTX 5080 GPU without paying an exorbitant markup. If you were to try to find a 5080 GPU for your do-it-yourself PC build, you'll probably spend nearly as much for the GPU as you would for an entire system.Alienware Aurora RTX 5080 Gaming PC From $2,450Alienware Aurora R16 Intel Core Ultra 7 265F RTX 5080 Gaming PC (16GB/1TB)$2,449.99 at AlienwareAlienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PC (32GB/2TB)Alienware Aurora R16 Intel Core Ultra 9 285K RTX 5080 Gaming PC (64GB/4TB)New for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PC (32GB/1TB)The prices on the Alienware Aurora R16 model starts range from the bottom end of $2,349.99 to the top end of $3,149.99. Each tier up offers either a CPU upgrade or increased RAM and/or storage:$2,349.99 - Intel Core Ultra 7 265F, 16GB RAM, 1TB SSD$2,799.99 - Intel Core Ultra 9 285K, 32GB RAM, 2TB SSD$3,249.99 - Intel Core Ultra 9 285K, 64GB RAM, 4TB SSDAlienware Area-51 RTX 5080 Gaming PC for $3,599.99New for 2025Alienware Area-51 Intel Core Ultra 7 265 RTX 5080 Gaming PC (32GB/1TB)Dell unveiled the new Alienware Area-51 gaming PC at CES 2025. The chassis looks similar to the 2024 R16 system with aesthetic and cooling redesigns and updated components. The I/O panel is positioned at the top of the case instead of the front, and the tempered glass window now spans the entire side panel instead of just a smaller cutout. As a result, the side panel vents are gone, and instead air intakes are located at the bottom as well as the front of the case. Alienware is now pushing a positive airflow design (more intake than exhaust airflow), which means a less dusty interior. The internal components have been refreshed with a new motherboard, faster RAM, and more powerful power supply to accommodate the new generation of CPUs and GPUs.The GeForce RTX 5080 GPU will run any game in 4KThe RTX 5080 is the second best Blackwell graphics card, surpassed only by the $2,000 RTX 5090. It's about 5%-10% faster than the previous generation RTX 4080 Super, which is discontinued and no longer available. In games that support the new DLSS 4 with multi-frame generation exclusive to Blackwell cards, the gap widens.Nvidia GeForce RTX 5080 FE Review, by Jacqueline Thomas"If you already have a high-end graphics card from the last couple of years, the Nvidia GeForce RTX 5080 doesn’t make a lot of sense – it just doesn’t have much of a performance lead over the RTX 4080, though the extra frames from DLSS 4 Multi-Frame Generation do make things look better in games that support it. However, for gamers with an older graphics card who want a significant performance boost, the RTX 5080 absolutely provides – doubly so if you’re comfortable with Nvidia’s AI goodies."Eric Song is the IGN commerce manager in charge of finding the best gaming and tech deals every day. When Eric isn't hunting for deals for other people at work, he's hunting for deals for himself during his free time.
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  • NVIDIA Blackwell Delivers Breakthrough Performance in Latest MLPerf Training Results

    NVIDIA is working with companies worldwide to build out AI factories — speeding the training and deployment of next-generation AI applications that use the latest advancements in training and inference.
    The NVIDIA Blackwell architecture is built to meet the heightened performance requirements of these new applications. In the latest round of MLPerf Training — the 12th since the benchmark’s introduction in 2018 — the NVIDIA AI platform delivered the highest performance at scale on every benchmark and powered every result submitted on the benchmark’s toughest large language model-focused test: Llama 3.1 405B pretraining.
    The NVIDIA platform was the only one that submitted results on every MLPerf Training v5.0 benchmark — underscoring its exceptional performance and versatility across a wide array of AI workloads, spanning LLMs, recommendation systems, multimodal LLMs, object detection and graph neural networks.
    The at-scale submissions used two AI supercomputers powered by the NVIDIA Blackwell platform: Tyche, built using NVIDIA GB200 NVL72 rack-scale systems, and Nyx, based on NVIDIA DGX B200 systems. In addition, NVIDIA collaborated with CoreWeave and IBM to submit GB200 NVL72 results using a total of 2,496 Blackwell GPUs and 1,248 NVIDIA Grace CPUs.
    On the new Llama 3.1 405B pretraining benchmark, Blackwell delivered 2.2x greater performance compared with previous-generation architecture at the same scale.
    On the Llama 2 70B LoRA fine-tuning benchmark, NVIDIA DGX B200 systems, powered by eight Blackwell GPUs, delivered 2.5x more performance compared with a submission using the same number of GPUs in the prior round.
    These performance leaps highlight advancements in the Blackwell architecture, including high-density liquid-cooled racks, 13.4TB of coherent memory per rack, fifth-generation NVIDIA NVLink and NVIDIA NVLink Switch interconnect technologies for scale-up and NVIDIA Quantum-2 InfiniBand networking for scale-out. Plus, innovations in the NVIDIA NeMo Framework software stack raise the bar for next-generation multimodal LLM training, critical for bringing agentic AI applications to market.
    These agentic AI-powered applications will one day run in AI factories — the engines of the agentic AI economy. These new applications will produce tokens and valuable intelligence that can be applied to almost every industry and academic domain.
    The NVIDIA data center platform includes GPUs, CPUs, high-speed fabrics and networking, as well as a vast array of software like NVIDIA CUDA-X libraries, the NeMo Framework, NVIDIA TensorRT-LLM and NVIDIA Dynamo. This highly tuned ensemble of hardware and software technologies empowers organizations to train and deploy models more quickly, dramatically accelerating time to value.
    The NVIDIA partner ecosystem participated extensively in this MLPerf round. Beyond the submission with CoreWeave and IBM, other compelling submissions were from ASUS, Cisco, Dell Technologies, Giga Computing, Google Cloud, Hewlett Packard Enterprise, Lambda, Lenovo, Nebius, Oracle Cloud Infrastructure, Quanta Cloud Technology and Supermicro.
    Learn more about MLPerf benchmarks.
    #nvidia #blackwell #delivers #breakthrough #performance
    NVIDIA Blackwell Delivers Breakthrough Performance in Latest MLPerf Training Results
    NVIDIA is working with companies worldwide to build out AI factories — speeding the training and deployment of next-generation AI applications that use the latest advancements in training and inference. The NVIDIA Blackwell architecture is built to meet the heightened performance requirements of these new applications. In the latest round of MLPerf Training — the 12th since the benchmark’s introduction in 2018 — the NVIDIA AI platform delivered the highest performance at scale on every benchmark and powered every result submitted on the benchmark’s toughest large language model-focused test: Llama 3.1 405B pretraining. The NVIDIA platform was the only one that submitted results on every MLPerf Training v5.0 benchmark — underscoring its exceptional performance and versatility across a wide array of AI workloads, spanning LLMs, recommendation systems, multimodal LLMs, object detection and graph neural networks. The at-scale submissions used two AI supercomputers powered by the NVIDIA Blackwell platform: Tyche, built using NVIDIA GB200 NVL72 rack-scale systems, and Nyx, based on NVIDIA DGX B200 systems. In addition, NVIDIA collaborated with CoreWeave and IBM to submit GB200 NVL72 results using a total of 2,496 Blackwell GPUs and 1,248 NVIDIA Grace CPUs. On the new Llama 3.1 405B pretraining benchmark, Blackwell delivered 2.2x greater performance compared with previous-generation architecture at the same scale. On the Llama 2 70B LoRA fine-tuning benchmark, NVIDIA DGX B200 systems, powered by eight Blackwell GPUs, delivered 2.5x more performance compared with a submission using the same number of GPUs in the prior round. These performance leaps highlight advancements in the Blackwell architecture, including high-density liquid-cooled racks, 13.4TB of coherent memory per rack, fifth-generation NVIDIA NVLink and NVIDIA NVLink Switch interconnect technologies for scale-up and NVIDIA Quantum-2 InfiniBand networking for scale-out. Plus, innovations in the NVIDIA NeMo Framework software stack raise the bar for next-generation multimodal LLM training, critical for bringing agentic AI applications to market. These agentic AI-powered applications will one day run in AI factories — the engines of the agentic AI economy. These new applications will produce tokens and valuable intelligence that can be applied to almost every industry and academic domain. The NVIDIA data center platform includes GPUs, CPUs, high-speed fabrics and networking, as well as a vast array of software like NVIDIA CUDA-X libraries, the NeMo Framework, NVIDIA TensorRT-LLM and NVIDIA Dynamo. This highly tuned ensemble of hardware and software technologies empowers organizations to train and deploy models more quickly, dramatically accelerating time to value. The NVIDIA partner ecosystem participated extensively in this MLPerf round. Beyond the submission with CoreWeave and IBM, other compelling submissions were from ASUS, Cisco, Dell Technologies, Giga Computing, Google Cloud, Hewlett Packard Enterprise, Lambda, Lenovo, Nebius, Oracle Cloud Infrastructure, Quanta Cloud Technology and Supermicro. Learn more about MLPerf benchmarks. #nvidia #blackwell #delivers #breakthrough #performance
    NVIDIA Blackwell Delivers Breakthrough Performance in Latest MLPerf Training Results
    blogs.nvidia.com
    NVIDIA is working with companies worldwide to build out AI factories — speeding the training and deployment of next-generation AI applications that use the latest advancements in training and inference. The NVIDIA Blackwell architecture is built to meet the heightened performance requirements of these new applications. In the latest round of MLPerf Training — the 12th since the benchmark’s introduction in 2018 — the NVIDIA AI platform delivered the highest performance at scale on every benchmark and powered every result submitted on the benchmark’s toughest large language model (LLM)-focused test: Llama 3.1 405B pretraining. The NVIDIA platform was the only one that submitted results on every MLPerf Training v5.0 benchmark — underscoring its exceptional performance and versatility across a wide array of AI workloads, spanning LLMs, recommendation systems, multimodal LLMs, object detection and graph neural networks. The at-scale submissions used two AI supercomputers powered by the NVIDIA Blackwell platform: Tyche, built using NVIDIA GB200 NVL72 rack-scale systems, and Nyx, based on NVIDIA DGX B200 systems. In addition, NVIDIA collaborated with CoreWeave and IBM to submit GB200 NVL72 results using a total of 2,496 Blackwell GPUs and 1,248 NVIDIA Grace CPUs. On the new Llama 3.1 405B pretraining benchmark, Blackwell delivered 2.2x greater performance compared with previous-generation architecture at the same scale. On the Llama 2 70B LoRA fine-tuning benchmark, NVIDIA DGX B200 systems, powered by eight Blackwell GPUs, delivered 2.5x more performance compared with a submission using the same number of GPUs in the prior round. These performance leaps highlight advancements in the Blackwell architecture, including high-density liquid-cooled racks, 13.4TB of coherent memory per rack, fifth-generation NVIDIA NVLink and NVIDIA NVLink Switch interconnect technologies for scale-up and NVIDIA Quantum-2 InfiniBand networking for scale-out. Plus, innovations in the NVIDIA NeMo Framework software stack raise the bar for next-generation multimodal LLM training, critical for bringing agentic AI applications to market. These agentic AI-powered applications will one day run in AI factories — the engines of the agentic AI economy. These new applications will produce tokens and valuable intelligence that can be applied to almost every industry and academic domain. The NVIDIA data center platform includes GPUs, CPUs, high-speed fabrics and networking, as well as a vast array of software like NVIDIA CUDA-X libraries, the NeMo Framework, NVIDIA TensorRT-LLM and NVIDIA Dynamo. This highly tuned ensemble of hardware and software technologies empowers organizations to train and deploy models more quickly, dramatically accelerating time to value. The NVIDIA partner ecosystem participated extensively in this MLPerf round. Beyond the submission with CoreWeave and IBM, other compelling submissions were from ASUS, Cisco, Dell Technologies, Giga Computing, Google Cloud, Hewlett Packard Enterprise, Lambda, Lenovo, Nebius, Oracle Cloud Infrastructure, Quanta Cloud Technology and Supermicro. Learn more about MLPerf benchmarks.
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